Phantom Data for Machine-Learning Aided Optical Imaging of Skin Tissue

Phantom data for spatial frequency domain imaging (sd-SFDI) used in research on cancerous and normal skin tissue. The dataset was contributed by Andrew Stier and hosted by the Texas Data Repository, with a last recorded update on March 18, 2024. The data likely contains optical property measurements from tissue-simulating phantoms.

Use Cases

• Training machine learning models to classify tissue types based on sub-diffuse optical properties.
• Calibrating or validating spatial frequency domain imaging (SFDI) systems using phantom measurements.
• Studying the relationship between optical scattering/absorption and tissue malignancy in a controlled setting.

Strengths

• Dataset is associated with a specific, peer-reviewed research method (spatial frequency domain imaging).
• Hosted on an institutional repository (Texas Data Repository), suggesting academic provenance.
• Last updated date is precisely recorded (2024-03-18 05:50:45).

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count and file size are unknown, which may limit suitability assessment.

Provenance

Source

Texas Data Repository Harvested Dataverse

Collection Method

Spatial frequency domain imaging (sd-SFDI) of tissue-simulating phantoms.

Time Range

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Freshness

Last updated 2024-03-18 05:50:45; freshness should be verified.

Geography

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